Small Object Detection Algorithm Based on Improved YOLOv8 for Remote Sensing

Due to the limitations of small targets in remote sensing images such as background noise, poor information, and so on, the results of commonly used detection algorithms in small target detection is not satisfactory. To improve the accuracy of detection results, we develop an improved algorithm based on YOLOv8, called LAR-YOLOv8. First, in the feature extraction network, the local module is enhanced by using the dual-branch architecture attention mechanism, while the vision transformer block is used to maximize the representation of the feature map. Second, an attention-guided bi-directional feature pyramid network is designed to generate more discriminative information by efficiently extracting feature from…

• NN
  National Natural Science Foundation of China

  Award: 62375266
• CA
  Chinese Academy of Sciences